class_docstr: The multi dimensional Brownian Motion.
class_docstr_tok: ["The","multi","dimensional","Brownian","Motion","."]
docstr: The total covariance of the process between two times.
  
  Returns:
    A Python callable returning the integrated covariances between two times.
    The callable accepts two real `Tensor` arguments. The first argument
    is the left end point and the second is the right end point of the time
    interval for which the total covariance is needed.
  
    The shape of the two input arguments and their dtypes must match.
    The output of the callable is a `Tensor` of shape
    `times_shape + [dim, dim]` containing the integrated covariance matrix
    between the start times and end times.
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code: def total_covariance_fn(self):
      """The total covariance of the process between two times.
  
      Returns:
        A Python callable returning the integrated covariances between two times.
        The callable accepts two real `Tensor` arguments. The first argument
        is the left end point and the second is the right end point of the time
        interval for which the total covariance is needed.
  
        The shape of the two input arguments and their dtypes must match.
        The output of the callable is a `Tensor` of shape
        `times_shape + [dim, dim]` containing the integrated covariance matrix
        between the start times and end times.
      """
      return self._total_covariance_fn
  
file_path: tf-quant-finance/tf_quant_finance/models/legacy/brownian_motion.py
imports: import tensorflow.compat.v2
  from tf_quant_finance.math.random_ops import multivariate_normal
  from tf_quant_finance.models.legacy import brownian_motion_utils
  from tf_quant_finance.models.legacy import ito_process
label_desc: Use image node_id 8 for calling the BrownianMotion obj's underlying member method code with example usage: obj.total_covariance_fn() and returns: self